RRepoGEO

REPOGEO REPORT · LITE

srush/MiniChain

Default branch main · commit 637d310c · scanned 6/28/2026, 6:51:35 PM

GitHub: 1,233 stars · 76 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface srush/MiniChain, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Strengthen README opening to clarify its role as an LLM orchestration framework

    Why:

    CURRENT
    A tiny library for coding with **large** language models.
    COPY-PASTE FIX
    MiniChain is a tiny, minimalist Python library for building robust, composable applications by chaining large language model calls. It provides a type-safe framework for orchestrating LLM prompts and debugging complex chains.
  • mediumreadme#2
    Add a brief comparison to other LLM frameworks in the README

    Why:

    COPY-PASTE FIX
    ## Why MiniChain?
While larger frameworks like LangChain offer extensive features, MiniChain focuses on a minimalist, functional approach to LLM application development, leveraging pure Python functions and decorators for composable chains. It's designed for developers who prefer a lightweight, type-safe alternative.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface srush/MiniChain
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. run-llama/llama_index · recommended 1×
  3. deepset-ai/haystack · recommended 1×
  4. PrefectHQ/marvin · recommended 1×
  5. microsoft/guidance · recommended 1×
  • CATEGORY QUERY
    How can I build complex applications by chaining large language model calls in Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. Marvin (PrefectHQ/marvin)
    5. Guidance (microsoft/guidance)
    6. Instructor (jxnl/instructor)
    7. Transformers Agents (huggingface/transformers)

    AI recommended 7 alternatives but never named srush/MiniChain. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Python frameworks for orchestrating LLM prompts and debugging chains?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Guidance
    5. DSPy
    6. LiteLLM

    AI recommended 6 alternatives but never named srush/MiniChain. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of srush/MiniChain?
    pass
    AI named srush/MiniChain explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts srush/MiniChain in production, what risks or prerequisites should they evaluate first?
    pass
    AI named srush/MiniChain explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo srush/MiniChain solve, and who is the primary audience?
    pass
    AI named srush/MiniChain explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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srush/MiniChain — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite